My modeling work began with my Master’s Thesis work at Rensselaer Polytechnic Institute in the early 1970s. As part of the International Biological Program, we developed models to simulate food web interactions in Lake George, NY and Lake Wingra, WI. My doctoral dissertation at the University of Michigan focused on use of Kalman Filtering (an early form of Bayesian estimation) to quantify and evaluate the dynamics of error propagation and uncertainty in eutrophication models. While at NOAA’s Great Lakes Environmental Research (1975-1990), I developed a set of ecological models for Lakes Ontario and Michigan focused on simulating the dynamics of their lower food webs in one, two, and three physical dimensions and exploring the bottom-up effects of changes in nutrient loading and the top-down effects of changes in fish populations. More recently, I have been using simpler models to explore and predict the effects of changes in nutrient loads on development of low-oxygen regions in coastal systems such as the northern Gulf of Mexico, the Chesapeake Bay, and Lake Erie.
Bocaniov, S.A., P. Van Cappellen, D. Scavia. On the role of a large shallow lake (Lake St. Clair, USA-Canada) in modulating phosphorus loads to Lake Erie. Water Resources Res. 10.1029/2019WR025019
Xu, X., Y-C Wang, M. Kalcic, R. L. Muenich, Y.C.E. Yang, D. Scavia. 2019. Evaluating the impact of climate change on fluvial flood risk in a mixed-use watershed. Environmental Modeling and Software. 122:1-11
Scavia, D. Time to pick up our heads and look inland. Limnol. Oceanogr. Bulletin November 2019
Scavia, D., S. Bocaniov, A. Dagnew, Y. Hu, B. Kerkez, C. Long, R. Muenich, J. Read, L. Vaccaro, Y-C. Wang. Detroit River phosphorus loads: Anatomy of a binational watershed, J Great Lakes Res. https://doi.org/10.1016/j.jglr.2019.09.008
Hu, Y., C.M. Long. Y-C Wang, B.Kerkez, D.Scavia. Urban Total Phosphorus Loads to the St. Clair-Detroit River System. J. Great Lakes Res. https://doi.org/10.1016/j.jglr.2019.09.009
Fang, S., D.D. Giudice, D. Scavia, C.E. Binding, T. B. Bridgeman, J. D. Chaffin, M. A. Evans, J. Guinness, T. H. Johengen, D. R. Obenour. A Space-time geostatistical model for probabilistic estimation of harmful algal bloom biomass and areal extent. Science of the Total Environment https://doi.org/10.1016/j.scitotenv.2019.133776
Kalcic, M.M., R. L. Muenich, S. Basile, A. L. Steiner, C. Kirchhoff, D. Scavia. 2019 Climate change and nutrient loading: warming can counteract a wetter future. Environ. Sci. Technol.
Dagnew, A. D. Scavia, Y-C Wang, R. Muenich, C. Long, M. Kalcic. 2019 Modeling Nutrient and Sediment Delivery from a Complex International Watershed with Highly Variable Land Cover. JAWRA https://doi.org/10.1111/1752-1688.12779
Scavia, D., S. Bocaniov, A. Dagnew, Y. Hu, B. Kerkez, C. Long, R. Muenich, J. Read, L. Vaccaro and Y. Wang. 2019. Watershed Assessment of Detroit River Phosphorus Loads to Lake Erie. Final project report produced by the University of Michigan Water Center.
Dagnew, A., D. Scavia, Y-C Wang, R.Muenich, M.Kalcic. 2019. Modeling phosphorus reduction strategies from the international St. Clair-Detroit River system watershed. J. Great Lakes Res. https://doi.org/10.1016/j.jglr.2019.04.005
Manning, N.F., Y.C. Wang, C. M. Long, I. Bertani, M. J. Sayers, K. R. Bosse, R. A. Shuchman, D. Scavia. 2019 Extending the Forecast Model: Predicting Harmful Algal Blooms at Multiple Spatial Scales. J. Great Lakes Res. 45:587–595 https://doi.org/10.1016/j.jglr.2019.03.004
Scavia, D. 2019. Sustainability in a politically polarized society. Michigan J. Sustainability 6 (1)
Scavia, D., D. Justic, D. Obenour, K. Craig, L. Wang. 2019. Hypoxic volume is more responsive than hypoxic area to nutrient load reductions in the northern Gulf of Mexico – and it matters to fish and fisheries. Env. Res. Lett.
Scavia, D., S.A. Bocaniov, A. Dagnew, C. Long, Y-C Wang. 2019. St. Clair-Detroit River system: Phosphorus mass balance and implications for Lake Erie load reduction, monitoring, and climate change. J. Great Lakes Res. 45:40-49
Hu, Y., D. Scavia, B.Kerkez. 2018. Are all data useful? Inferring causality to predict flows across sewer and drainage systems using Directed Information and Boosted Regression Trees. Water Res. 145: 697-706
Bocaniov, S. A. and D. Scavia. 2018. Nutrient loss rates in relation to transport time scales in a large shallow lake (Lake St. Clair, USA – Canada): insights from a three-dimensional lake model. Water Resources. Res. 54: 3825-3840
Del Giudice, D., R.L. Muenich, M. Kalcic, N.S. B., D. Scavia, A. M. Michalak. 2018. On the practical usefulness of least squares for assessing uncertainty in hydrologic and water quality predictions. Env. Modeling and Software 105: 286–295
Long, C., R. L. Muenich, M. Kalcic, D. Scavia. 2018. Use of manure nutrients from Concentrated Animal Feeding Operations. J. Great Lakes. Res. 44: 245–252
Muenich, R.L., M.M. Kalcic, J. Winsten, K. Fisher, M. Day, G. O’Neil, Y.-C. Wang, D. Scavia. 2017. Pay-For-Performance Conservation Using SWAT Highlights Need for Field-Level Agricultural Conservation. Trans. ASABE. 60:1925-1937
Scavia, D., I. Bertani, D.R. Obenour, R.E. Turner, D.R. Forrest, A. Katin. 2017 Ensemble modeling informs hypoxia management in the northern Gulf of Mexico. Proc. Nat. Acad. Sci. 114:8823-8828
Lipor, J., B. Wong, D. Scavia, B. Kerkez, L. Balzano, 2017. Distance-penalized active learning algorithm using quantile search. IEEE Trans. Signal Processing. https://doi.org/10.1109/TSP.2017.2731323
Testa, J.M., J.B. Clark, W.C. Dennison, E.C. Donovan, A.W. Fisher, W. Ni, M. Parker, D. Scavia, S.E. Spitzer, A.M. Waldrop, V.M.D. Vargas, G. Ziegler. 2017 Ecological forecasting and the science of hypoxia in Chesapeake Bay BioScience. 67: 614-626
Scavia, D., M. Kalcic, R. Logsdon Muenich, N. Aloysius, I. Bertani, C. Boles, R. Confesor, J. DePinto, M. Gildow, J. Martin, J. Read, T. Redder, D. Robertson, S. Sowa, Y. Wang, H Yen. 2017 Multiple models guide strategies for agricultural nutrient reductions. Frontiers in Ecology and the Environment. 15: 126–132
Bertani, I., C. E. Steger, D. R. Obenour, G. L. Fahnenstiel, T. B. Bridgeman, T. H. Johengen, M. J. Sayers, R. A. Shuchman, D. Scavia. 2016. Tracking cyanobacteria blooms: do different monitoring approaches tell the same story? Science of the Total Environment 575: 294-308
Scavia, D., J.V. DePinto, I. Bertani. 2016. A Multi-model approach to evaluating target phosphorus loads for Lake Erie. J. Great Lakes Res. in press
Zhang, H., L. Boegman, D. Scavia, D. A. Culver. 2016. Spatial distributions of external and internal phosphorus loads in Lake Erie and their impacts on phytoplankton and water quality. J Great Lakes Res. in press
Bocaniov, S.A, L.F. Keon, Y.R. Rao, D.J. Schwab, D. Scavia. 2016 Simulating the effect of nutrient reduction on hypoxia in a large lake (Lake Erie, USA-Canada) with a three-dimensional lake model. J. Great Lakes. Res http://dx.doi.org/10.1016/j.jglr.2016.06.001
Kalcic, M., Kirchhoff, N. Bosch, R. L. Muenich, M. Murray, , J. Gardner. D. Scavia. 2016. Engaging stakeholders to define feasible and desirable agricultural conservation in western Lake Erie watersheds. Env. Sci. Technol. in press DOI: 10.1021/acs.est.6b01421
Muenich, R.L., M. Kalcic, D. Scavia. 2016. Evaluating the impact of legacy P and agricultural conservation practices on nutrient loads from the Maumee River Watershed. Env. Sci. Technol. in press DOI: 10.1021/acs.est.6b01420
Rucinski, D., DePinto, J., Beletsky, D., Scavia, D. 2016 Modeling hypoxia in the Central Basin of Lake Erie under potential phosphorus load reduction scenarios. J. Great. Lakes Res. in press
Bocaniov, S. and D. Scavia 2016 Temporal and spatial dynamics of large lake hypoxia: Integrating statistical and three-dimensional dynamic models to enhance lake management criteria. Water Resources Res. (Supplemental Information) in press
Bertani, I, D.R. Obenour, C. E. Steger, C. A. Stow, A. D. Gronewold, D. Scavia 2016 Probabilistically assessing the role of nutrient loading in harmful algal bloom formation in western Lake Erie. J Great Lakes. Res. in press
Lipor, J., L. Balzano, B. Kerkez, D. Scavia. 2015. Quantile Search: A Distance-Penalized Active Learning Algorithm for Spatial Sampling. Proc. 53rd Annual Allerton Conf. on Communication, Control, and Computing.
Obenour, D.R., A M. Michalak, and D. Scavia 2015 Assessing biophysical controls on Gulf of Mexico hypoxia through probabilistic modeling. Ecol. Applicationshttp://dx.doi.org/10.1890/13-2257.1
Obenour, D.R. A.D. Gronewold, C.A. Stow, and D. Scavia 2014 Using a Bayesian hierarchical model with a gamma error distribution to improve Lake Erie cyanobacteria bloom forecasts. Water Resources Res.
Obenour, D.R., A M. Michalak, and D. Scavia 2015 Assessing biophysical controls on Gulf of Mexico hypoxia through probabilistic modeling. Ecol. Applications http://dx.doi.org/10.1890/13-2257.1
Daloglu, I. J.I. Nassauer, R.L. Riolo, D. Scavia 2014 Developing a farmer typology to link agent-based models with SWAT Agricultural Systems
Bosch, N.S., M.A. Evans, D. Scavia, J.D. Allan 2014 Interacting effects of climate change and agricultural BMPs on nutrient runoff. J. Great Lakes Res.
Scavia, D., J. D. Allan, K. K. Arend, S. Bartell, D. Beletsky, N. S. Bosch, S. B. Brandt, R. D. Briland, I. Daloğlu, J. V. DePinto, D. M. Dolan, M. A. Evans, T. M. Farmer,D. Goto, H. Han, T. O. Höök, R. Knight, S. A. Ludsin, D. Mason, A. M. Michalak, R. P. Richards, J. J. Roberts, D. K. Rucinski, E. Rutherford, D. J. Schwab, T. Sesterhenn, H. Zhang, Y. Zhou. 2014 Assessing and addressing the re-eutrophication of Lake Erie: Central Basin Hypoxia. J. Great Lakes Res. 40: 226–246. http://dx.doi.org/10.1016/j.jglr.2014.02.004
Michalak, A.M., E. Anderson, D. Beletsky, S. Boland, N.S. Bosch, T.B. Bridgeman, J.D. Chaffin, K.H. Cho, R. Confesor, I. Daloglu, J. DePinto, M.A. Evans, G.L. Fahnenstiel, L. He, J.C. Ho, L. Jenkins, T. Johengen, K.C. Kuo, E. Laporte, X. Liu, M. McWilliams, M.R. Moore, D.J. Posselt, R.P. Richards, D. Scavia, A.L. Steiner, E. Verhamme8, D.M. Wright, M.A. ZagorskiÂ 2013 Record-setting algal bloom in Lake Erie caused by agricultural and meteorological trends consistent with expected future conditions. Proc. Nat. Acad. Sci. 110 (16) 6448-6452 Supporting Information
Rucinski, D., D. Scavia, J. DePinto, D. Beletsky 2014 Lake Erie’s hypoxia response to nutrient loads and meteorological variability. J. Great Lakes Res.
Daloglu, I. J.I. Nassauer, R.L. Riolo, D. Scavia 2014 An Integrated Social and Ecological Modeling Framework – Impacts of Agricultural Conservation Practices on Water Quality. Ecology and Society
Zhou, Y., D. Scavia, A.M. Michalak 2014 Nutrient loading and meteorological conditions explain interannual variability of hypoxia in the Chesapeake Bay. Limnol. Oceanogr. 59:373-374
Scavia, D., M.A. Evans, D. Obenour 2013A scenario and forecast model for Gulf of Mexico hypoxic area and volume. Environ. Sci. Technol.http://dx.doi.org/10.1021/es4025035
Obenour, D.; D. Scavia, N.R. Rabalais; E.R. Turner; A. Michalak 2013 A retrospective analysis of mid-summer hypoxic area and volume in the northern Gulf of Mexico, 1985-2011 Environ. Sci. Technol. Supporting Information
Bosch N.S., J.D. Allan, J.P. Selegean, D. Scavia 2013 Scenario-testing of agricultural best management practices in Lake Erie watersheds. J. Great Lakes. Res. Supporting Information
Evans, M.A. and D. Scavia 2013 Exploring estuarine eutrophication sensitivity to nutrient loading. Limnol. Oceanogr.
Zhou, Y., D.R. Obenour, D. Scavia, T.H. Johengen, A.M. Michalak (2013) Spatial and Temporal Trends in Lake Erie Hypoxia, 1987-2007. Environ. Sci. Technol.47 (2), pp 899-905 Supporting Information; Correction
Richards, R. P., I. Alameddine, J.D. Allan , D.B. Baker, N. S. Bosch, R. Confesor, J.V. DePinto, D.M. Dolan, J.M. Reutter, D. Scavia 2012 Nutrient Inputs to the Laurentian Great Lakes by Source and Watershed Estimated Using SPARROW Watershed Models. J. Am. Water Res. Assoc.
Daloglu, I. K.H. Cho, D. Scavia 2012 Evaluating causes of trends in long-term dissolved reactive phosphorus loads to Lake Erie. Environ. Sci. Technol. 46:10660-10666
Obenour, D.R., A.M. Michalak,Y. Zhou, and D. Scavia. 2012. Quantifying the Impacts of Stratification and Nutrient Loading on Hypoxia in the Northern Gulf of Mexico. Environ. Sci. Technol. dxdoi.org/10.102/es204481a
Liu, Y., G.B. Arhonditsis, C. Stow, D. Scavia. 2011 Comparing Chesapeake Bay Hypoxic-Volume and Dissolved-Oxygen Profile Predictions with A Bayesian Streeter-Phelps Model. J. America Water Res. Assoc.
Evans, M.A. and D. Scavia 2010. Forecasting hypoxia in the Chesapeake Bay and Gulf of Mexico: Model accuracy, precision, and sensitivity to ecosystem change. Environ. Res. Letters. doi:10.1088/1748-9326/6/1/015001 Associated News Summary
Bell, A., M. Lemos, and D. Scavia. 2010 . Cattle, Clean Water, and Climate Change: Policy Choices for the Brazilian Agricultural Frontier. Environ. Sci. Technol. 44(22): 8377-8384
Rucinski, D.K., D. Beletsky, J. V. DePinto, D. J. Schwab, D. Scavia. 2010 A Simple 1-Dimensional Climate Based Dissolved Oxygen Model for Central Basin of Lake Erie. J. Great Lakes Res. 36:465-476
Liu, Y, M.A. Evans, D. Scavia. 2010 Gulf of Mexico Hypoxia: Exploring Increasing Sensitivity to Nitrogen Loads. Environ. Sci. Technol.
Liu, Y. and D. Scavia. 2010. Analysis of the Chesapeake Bay Hypoxia Regime Shift: Insights from Two Simple Mechanistic Models. Estuaries and Coasts 33:629-639DOI 10.1007/s12237-009-9251-z
Fishman, D., S.A. Adlerstein,D. Scavia. 2010 Phytoplankton Community Composition of Saginaw Bay, Lake Huron, during the Zebra Mussel (Dreissena polymorpha) Invasion: A Multivariate Analysis J. Great Lakes Res. 36:1-19
Fishman, D., D. Scavia, S.A. Adlerstein.2009. Causes of Phytoplankton Changes in Saginaw Bay, Lake Huron during the Zebra Mussel Invasion. J. Great Lakes Res. 35: 482-495
Han. H., J. D. Allan, D. Scavia. 2009. Influence of Climate and Human Activities on the Relationship between Watershed Nitrogen Input and River Export. Environ. Sci. Technol. 43:1916-1922. Supporting Information
Stow, C.A. and D. Scavia. 2009. Modeling Hypoxia in the Chesapeake Bay: Ensemble Estimation Using a Bayesian Hierarchical Model. J. Marine Systems 76:244-250.
Scavia, D. and K.A. Donnelly. 2007. Reassesing Hypoxia Forecasts for the Gulf of Mexico. Env. Sci. Technol. 41, 8111â€“8117.Â Â Published Supporting Information
Justic, D., V.J. Bierman, Jr., D. Scavia. and R. Hetland. Forecasting Gulf’s Hypoxia: The Next 50 Years? 2007. Estuaries and Coasts, 30(5): 791-801.
Swaney, D.P., D. Scavia, R.W. Howarth, R.M. Marino. 2008 Estuarine Classification and Response to Nitrogen Loading: Insights from Simple Ecological Models. Estuarine and Continental Shelf Science Special Issue.
Donner, S.D and D. Scavia. 2007. How climate controls the flux of nitrogen by the Mississippi River and the development of hypoxia in the Gulf ofÂ Mexico. Limnol. Oceanogr. 52(2): 856-861.
Bierman, V.J. Jr., S.C. Hinz; D. Justic, D.Scavia, J.A. Veil, K. Satterlee, M. Parker. 2007. Predicted Impacts from Offshore Produced Water Discharges on Hypoxia in the Gulf of Mexico. SPE Facilities, Construction, and Operations.Â Society of Petroleum Engineers.
Scavia, D., E.A. Kelly, and J. D. Hagy III. 2006. A simple model for forecasting the effects of nitrogen loads on Chesapeake Bay hypoxia.Â Estuaries and Coasts 29(4) 674-684.
Scavia, D., D. Justic, and V.J. Bierman, Jr. 2004. Reducing hypoxia in the Gulf of Mexico: Advice from three models. Estuaries 27(3):419-425.
Scavia, D. N.N. Rabalais, R.E. Turner, D. Justic, and W. Wiseman Jr. 2003. Predicting the response of Gulf of Mexico Hypoxia to variations in Mississippi River Nitrogen Load. Limnol. Oceanogr. 48(3): 951-956.
Scavia, D., G.A. Lang, and J.F. Kitchell. 1988. Dynamics of Lake Michigan plankton: A model evaluation of nutrient loading, competition, predation. Can. J. Fish. Aquat. Sci., 45: 165 – 177
Fahnenstiel, G.L., D. Scavia, G.A. Lang, J. Saylor, G. Miller, and D.J. Schwab. 1988. Impact of internal waves on conventional primary production estimates. J. Plankton Res. 10: 77-87.
Henderson-Sellers, B., M.J. McCormick, and D. Scavia. 1983. A Comparison of the Formulation for Eddy Diffusion in two One-dimensional Stratification Models. Appl. Math.
McCormick, M.J. and D. Scavia. 1981. Calculation of Vertical Profiles of Lake Averaged Temperature and Diffusivity in Lakes Ontario and Washington. Water Resources Research 17:305-310.
Scavia, D., W. F. Powers, R. P. Canale, and J. L. Moody. 1981. Comparisons of First-Order Error Analysis and Monte Carlo Simulation in Time-dependent Lake Eutrophication Models. Water Resources Research 17:1051-1059.
Scavia, D., R.P. Canale, W. F. Powers, and J. L. Moody 1981. Variance Estimates for a Dynamic Eutrophication Model of Saginaw Bay, Lake Huron. Water Resources Research 17:1115-1124.
Scavia, D. 1980. An Ecological Model of Lake Ontario. Ecological Modelling 8:49-78.
Scavia, D. and J. R. Bennett. 1980. The Spring Transition Period of Lake Ontario – A Numerical Study of the Causes of the Large Biological and Chemical Gradients. Can. J. Fish. Aquat.Sci. 37:823-833.
Scavia, D. and A. Robertson. (Eds.) 1979. Perspectives on Lake Ecosystem Modeling. Ann Arbor Science Publ., Ann Arbor, 330p.
Vanderploeg, H.A. and D. Scavia. 1979. Calculation and Use of Selective Feeding Coefficients: Zooplankton Grazing. Ecological Modelling 7:135-150.
Vanderploeg, H.A. and D. Scavia. 1979. Two Electivity Indecies for Feeding With Special Reference To Zooplankton Grazing. J. Fish. Res. Bd. CanadaÂ 36:362-365.
Scavia, D. 1979. Examination of Phosphorus Cycling and Control of Phytoplankton Dynamics in Lake Ontario With An Ecological Model. J. Fish. Res. Bd. CanadaÂ 36:1336-1346.
Robertson, A. and D. Scavia 1978. Ecosystem and Water Quality Modeling During IFYGL. Verh. Internat. Verein. Limnol 20:311-316.
Scavia, D. and S. C. Chapra. 1977. Comparison of An Ecological Model of Lake Ontario and Phosphorus Loading Models. J. Fish. Res. Bd. Canada 34:286-290.
Scavia, D. and R. V. Thomann. 1977. Some Comments on a Water Quality Model for Deep Reservoirs. J. Water Pollution Control Federation 49:507.
Kohberger, R.C., D. Scavia, and J. W. Wilkinson. 1978. A Method for Parameter Sensitivity Analysis for Differential Equation Models. Water Resources Research 14:25-29.
Scavia, D. and R.A. Park. 1976. Documentation of Selected Constructs and Parameter Values in the Aquatic Model CLEANER. Ecological Modelling 2:33-58.
Scavia, D. and B. J. Eadie. 1976. Use of Measurable Coefficients in process Formulations-Zooplankton Grazing.Â Ecological Modeling 2:315-319.
Park, R.A., R.V. O’Neill, J.A. Bloomfield, H.H. Shugart, R.S. Booth, R.A. Goldstine, J.B. Mankin, J.F. Koonce, D. Scavia, M.S.Adams, L.S. Cleseri, E.M. Colon, E.H. Dettmann, J. Hoopes, D.D. Huff, S. Katz, J.F. Kitchell, R.C. Kohberger, E.J. Larow, D.C. McNaught, J. Petersen, J. Titus, P.R. Weiler, J.W. Wilkinson, C.S. Zahorcak. 1974. A Generalized Model for Simulating Lake Ecosystems. Simulation 23:51-56.